:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	He, Xingxin, Hu, Yifan, Zhou, Zhaoye, Jarraya, Mohamed, Liu, Fang
Format:	Preprint
Published:	2025
Subjects:	Computer Vision and Pattern Recognition
Online Access:	https://arxiv.org/abs/2501.09138
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

OmniMRI: A Unified Vision--Language Foundation Model for Generalist MRI Interpretation
by: He, Xingxin, et al.
Published: (2025)

Adapting Foundation Models for Few-Shot Medical Image Segmentation: Actively and Sequentially
by: Yang, Jingyun, et al.
Published: (2025)

SD-FSMIS: Adapting Stable Diffusion for Few-Shot Medical Image Segmentation
by: Li, Meihua, et al.
Published: (2026)

On the Utility of Foundation Models for Fast MRI: Vision-Language-Guided Image Reconstruction
by: Feng, Ruimin, et al.
Published: (2025)

RAP: Retrieve, Adapt, and Prompt-Fit for Training-Free Few-Shot Medical Image Segmentation
by: Mao, Zhihao, et al.
Published: (2026)

Rethinking Few-Shot Medical Image Segmentation by SAM2: A Training-Free Framework with Augmentative Prompting and Dynamic Matching
by: Zu, Haiyue, et al.
Published: (2025)

Contrastive Graph Modeling for Cross-Domain Few-Shot Medical Image Segmentation
by: Bo, Yuntian, et al.
Published: (2025)

Retrieval-augmented Few-shot Medical Image Segmentation with Foundation Models
by: Zhao, Lin, et al.
Published: (2024)

SynPo: Boosting Training-Free Few-Shot Medical Segmentation via High-Quality Negative Prompts
by: Liu, Yufei, et al.
Published: (2025)

Few-Shot Panoptic Segmentation With Foundation Models
by: Käppeler, Markus, et al.
Published: (2023)

Tied Prototype Model for Few-Shot Medical Image Segmentation
by: Kim, Hyeongji, et al.
Published: (2025)

PointSeg: A Training-Free Paradigm for 3D Scene Segmentation via Foundation Models
by: He, Qingdong, et al.
Published: (2024)

SegTTA: Training-Free Test-Time Augmentation for Zero-Shot Medical Imaging Segmentation
by: Yao, Yihong, et al.
Published: (2026)

Few-Shot Medical Image Segmentation with Large Kernel Attention
by: Wu, Xiaoxiao, et al.
Published: (2024)

Hypergraph-Enhanced Training-Free and Language-Free Few-Shot Anomaly Detection
by: Xie, Guohuan, et al.
Published: (2026)

DiffuSAM: Diffusion-Based Prompt-Free SAM2 for Few-Shot and Source-Free Medical Image Segmentation
by: Grossman, Tal, et al.
Published: (2026)

Learning Robust Correlation with Foundation Model for Weakly-Supervised Few-Shot Segmentation
by: Huang, Xinyang, et al.
Published: (2024)

Asymmetric Co-Training for Source-Free Few-Shot Domain Adaptation
by: Li, Gengxu, et al.
Published: (2025)

Few-Shot Medical Image Segmentation with High-Fidelity Prototypes
by: Tang, Song, et al.
Published: (2024)

VISTA3D: A Unified Segmentation Foundation Model For 3D Medical Imaging
by: He, Yufan, et al.
Published: (2024)

SAM-IF: Leveraging SAM for Incremental Few-Shot Instance Segmentation
by: Zhou, Xudong, et al.
Published: (2024)

HAAF: Hierarchical Adaptation and Alignment of Foundation Models for Few-Shot Pathology Anomaly Detection
by: Yang, Chunze, et al.
Published: (2026)

Concentrate on Weakness: Mining Hard Prototypes for Few-Shot Medical Image Segmentation
by: Jiang, Jianchao, et al.
Published: (2025)

High-Performance Few-Shot Segmentation with Foundation Models: An Empirical Study
by: Chang, Shijie, et al.
Published: (2024)

Zero-Training Task-Specific Model Synthesis for Few-Shot Medical Image Classification
by: Qin, Yao, et al.
Published: (2025)

ProtoSAM: One-Shot Medical Image Segmentation With Foundational Models
by: Ayzenberg, Lev, et al.
Published: (2024)

Dynamic Gradient Sparsification Training for Few-Shot Fine-tuning of CT Lymph Node Segmentation Foundation Model
by: Luo, Zihao, et al.
Published: (2025)

Efficient and Context-Aware Label Propagation for Zero-/Few-Shot Training-Free Adaptation of Vision-Language Model
by: Li, Yushu, et al.
Published: (2024)

MedSAMix: A Training-Free Model Merging Approach for Medical Image Segmentation
by: Yang, Yanwu, et al.
Published: (2025)

Regularized Low-Rank Adaptation for Few-Shot Organ Segmentation
by: Baklouti, Ghassen, et al.
Published: (2025)

Foundation Model-Powered 3D Few-Shot Class Incremental Learning via Training-free Adaptor
by: Ahmadi, Sahar, et al.
Published: (2024)

SAM3D: Zero-Shot Semi-Automatic Segmentation in 3D Medical Images with the Segment Anything Model
by: Chan, Trevor J., et al.
Published: (2024)

Temporal Evolution of Knee Osteoarthritis: A Diffusion-based Morphing Model for X-ray Medical Image Synthesis
by: Wang, Zhe, et al.
Published: (2024)

CAT-SAM: Conditional Tuning for Few-Shot Adaptation of Segment Anything Model
by: Xiao, Aoran, et al.
Published: (2024)

Textual and Visual Guided Task Adaptation for Source-Free Cross-Domain Few-Shot Segmentation
by: Liu, Jianming, et al.
Published: (2025)

SegGraph: Leveraging Graphs of SAM Segments for Few-Shot 3D Part Segmentation
by: Hu, Yueyang, et al.
Published: (2025)

Prototype Correlation Matching and Class-Relation Reasoning for Few-Shot Medical Image Segmentation
by: Zhang, Yumin, et al.
Published: (2024)

Is Foreground Prototype Sufficient? Few-Shot Medical Image Segmentation with Background-Fused Prototype
by: Tang, Song, et al.
Published: (2024)

A Novel Benchmark for Few-Shot Semantic Segmentation in the Era of Foundation Models
by: Bensaid, Reda, et al.
Published: (2024)

Boundary-Aware Test-Time Adaptation for Zero-Shot Medical Image Segmentation
by: Xu, Chenlin, et al.
Published: (2025)